Cyber-Physical Security of Air Traffic Surveillance Systems
Abstract
Cyber-physical system security is a significant concern in the critical infrastructure. Strong interdependencies between cyber and physical components render cyber-physical systems highly susceptible to integrity attacks such as injecting malicious data and projecting fake sensor measurements. Traditional security models partition cyber-physical systems into just two domains – high and low. This absolute partitioning is not well suited to cyber-physical systems because they comprise multiple overlapping partitions. Information flow properties, which model how inputs to a system affect its outputs across security partitions, are important considerations in cyber-physical systems. Information flows support traceability analysis that helps detect vulnerabilities and anomalous sources, contributing to the implementation of mitigation measures. This chapter describes an automated model with graph-based information flow traversal for identifying information flow paths in the Automatic Dependent Surveillance-Broadcast (ADS-B) system used in civilian aviation, and subsequently partitioning the flows into security domains. The results help identify ADS-B system vulnerabilities to failures and attacks, and determine potential mitigation measures.
Recommended Citation
A. Thudimilla and B. M. McMillin, "Cyber-Physical Security of Air Traffic Surveillance Systems," IFIP Advances in Information and Communication Technology, vol. 596, pp. 3 - 23, Springer Verlag, Jan 2020.
The definitive version is available at https://doi.org/10.1007/978-3-030-62840-6_1
Meeting Name
IFIP Advances in Information and Communication Technology
Department(s)
Computer Science
Keywords and Phrases
ADS-B system; Cyber-physical systems; integrity; privacy
International Standard Book Number (ISBN)
978-303062839-0
International Standard Serial Number (ISSN)
1868-4238; 1868-422X
Document Type
Article - Conference proceedings
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2020 Springer Verlag, All rights reserved.
Publication Date
01 Jan 2020
Comments
National Science Foundation, Grant CNS-1837472